This historic book may have numerous typos and missing text. Purchasers can usually download a free scanned copy of the original book (without typos) from the publisher. Not indexed. Not illustrated. 1873 edition. Excerpt:...but it does not follow that knowledge is not good. It is more needful that I should be a good Christian, than that I should be able to make good shoes. But this, too, is needful for one who is a shoemaker, and his Christianity is to show (...) itself in his earthly calling, and not to be an excuse for unskilfulness therein. And here, too, the case is similar. It is true that knowledge puffs up, that is, superficial knowledge, the appearance of knowledge, where its reality and solidity are wanting; while true knowledge, and earnest genuine research, makes a man humble and modest. For the more we learn, the more we perceive what we owe to others, and the more we know, the more we perceive how little we know. Heal research, moreover, is impossible without self-denial, devotion, and a feeling for truth which will not be ashamed to confess its errors to itself and others. To investigate is a moral labour, and not a mere exercise of the mind. True science cannot be separated from morality, and true morality has always a religious root, even when this is unconfessed. When we investigate, too, we owe our best discoveries to God; our best possessions are a gift from above. When Pythagoras had discovered his famous geometrical theorem concerning the squares of a right-angled triangle, he sacrificed a hecatomb to the gods. And Kepler concluded his famous work on the motion of the planets with hearty thanksgiving to God. The true disciples of science have ever been the pupils of that heavenly wisdom of which St. James says that it is " peaceable, gentle, easy to be entreated, without partiality, and without hypocrisy." And does not all knowledge, when we go deeply into it, lead is to God? What Bacon said of philosophy, that " a little inclineth mens minds... (shrink)

In the international bestseller, Thinking, Fast and Slow, Daniel Kahneman, the renowned psychologist and winner of the Nobel Prize in Economics, takes us on a groundbreaking tour of the mind and explains the two systems that drive the way we think. System 1 is fast, intuitive, and emotional; System 2 is slower, more deliberative, and more logical. The impact of overconfidence on corporate strategies, the difficulties of predicting what will make us happy in the future, the profound effect of cognitive (...) biases on everything from playing the stock market to planning our next vacation—each of these can be understood only by knowing how the two systems shape our judgments and decisions. -/- Engaging the reader in a lively conversation about how we think, Kahneman reveals where we can and cannot trust our intuitions and how we can tap into the benefits of slow thinking. He offers practical and enlightening insights into how choices are made in both our business and our personal lives—and how we can use different techniques to guard against the mental glitches that often get us into trouble. Winner of the National Academy of Sciences Best Book Award and the Los Angeles Times Book Prize and selected by The New York Times Book Review as one of the ten best books of 2011, Thinking, Fast and Slow is destined to be a classic. (shrink)

This article reviews the transition between post-Fregean anti-naturalistic epistemology and contemporary naturalistic epistemologies. It traces the revival of naturalism to Quine’s critique of the "a priori", and Kuhn’s defense of historicism, and use the arguments of Quine and Kuhn to identify a position, "traditional naturalism", that combines naturalistic themes with the claim that epistemology is a normative enterprise. Pleas for more radical versions of naturalism are articulated, and briefly confronted.

This is the classic work upon which modern-day game theory is based. What began as a modest proposal that a mathematician and an economist write a short paper together blossomed, when Princeton University Press published Theory of Games and Economic Behavior. In it, John von Neumann and Oskar Morgenstern conceived a groundbreaking mathematical theory of economic and social organization, based on a theory of games of strategy. Not only would this revolutionize economics, but the entirely new field of scientific inquiry (...) it yielded--game theory--has since been widely used to analyze a host of real-world phenomena from arms races to optimal policy choices of presidential candidates, from vaccination policy to major league baseball salary negotiations. And it is today established throughout both the social sciences and a wide range of other sciences. (shrink)

Knowledge in a Social World offers a philosophy for the information age. Alvin Goldman explores new frontiers by creating a thoroughgoing social epistemology, moving beyond the traditional focus on solitary knowers. Against the tides of postmodernism and social constructionism Goldman defends the integrity of truth and shows how to promote it by well-designed forms of social interaction. From science to education, from law to democracy, he shows why and how public institutions should seek knowledge-enhancing practices. The result is a bold, (...) timely, and systematic treatment of the philosophical foundations of an information society. (shrink)

Humans and animals make inferences about the world under limited time and knowledge. In contrast, many models of rational inference treat the mind as a Laplacean Demon, equipped with unlimited time, knowledge, and computational might. Following H. Simon's notion of satisficing, the authors have proposed a family of algorithms based on a simple psychological mechanism: one-reason decision making. These fast and frugal algorithms violate fundamental tenets of classical rationality: They neither look up nor integrate all information. By computer simulation, the (...) authors held a competition between the satisficing "Take The Best" algorithm and various "rational" inference procedures. The Take The Best algorithm matched or outperformed all competitors in inferential speed and accuracy. This result is an existence proof that cognitive mechanisms capable of successful performance in the real world do not need to satisfy the classical norms of rational inference. (shrink)

The paper shows why and how an empirical study of fast-and-frugal heuristics can provide norms of good reasoning, and thus how (and how far) rationality can be naturalized. We explain the heuristics that humans often rely on in solving problems, for example, choosing investment strategies or apartments, placing bets in sports, or making library searches. We then show that heuristics can lead to judgments that are as accurate as or even more accurate than strategies that use more information and computation, (...) including optimization methods. A standard way to defend the use of heuristics is by reference to accuracy-effort trade-offs. We take a different route, emphasizing ecological rationality (the relationship between cognitive heuristics and environment), and argue that in uncertain environments, more information and computation are not always better (the “less-can-be-more” doctrine). The resulting naturalism about rationality is thus normative because it not only describes what heuristics people use, but also in which specific environments one should rely on a heuristic in order to make better inferences. While we desist from claiming that the scope of ecological rationality is unlimited, we think it is of wide practical use. (shrink)

Traditional analyses of the curve fitting problem maintain that the data do not indicate what form the fitted curve should take. Rather, this issue is said to be settled by prior probabilities, by simplicity, or by a background theory. In this paper, we describe a result due to Akaike [1973], which shows how the data can underwrite an inference concerning the curve's form based on an estimate of how predictively accurate it will be. We argue that this approach throws light (...) on the theoretical virtues of parsimoniousness, unification, and non ad hocness, on the dispute about Bayesianism, and on empiricism and scientific realism. * Both of us gratefully acknowledge support from the Graduate School at the University of Wisconsin-Madison, and NSF grant DIR-8822278 (M.F.) and NSF grant SBE-9212294 (E.S.). Special thanks go to A. W. F. Edwards.William Harper. Martin Leckey. Brian Skyrms, and especially Peter Turney for helpful comments on an earlier draft. (shrink)

This article described three heuristics that are employed in making judgements under uncertainty: representativeness, which is usually employed when people are asked to judge the probability that an object or event A belongs to class or process B; availability of instances or scenarios, which is often employed when people are asked to assess the frequency of a class or the plausibility of a particular development; and adjustment from an anchor, which is usually employed in numerical prediction when a relevant value (...) is available. These heuristics are highly economical and usually effective, but they lead to systematic and predictable errors. A better understanding of these heuristics and of the biases to which they lead could improve judgements and decisions in situations of uncertainty. (shrink)

Standard Analytic Epistemology (SAE) names a contingently clustered class of methods and theses that have dominated English-speaking epistemology for about the past half-century. The major contemporary theories of SAE include versions of foundationalism, coherentism, reliabilism, and contextualism. While proponents of SAE don’t agree about how to define naturalized epistemology, most agree that a thoroughgoing naturalism in epistemology can’t work. For the purposes of this paper, we will suppose that a naturalistic theory of epistemology takes as its core, as its starting-point, (...) an empirical theory. The standard argument against naturalistic approaches to epistemology is that empirical theories are essentially descriptive, while epistemology is essentially prescriptive, and a descriptive theory cannot yield normative, evaluative prescriptions. In short, naturalistic theories cannot overcome the is-ought divide. Our main goal in this paper is to show that the standard argument against naturalized epistemology has it almost exactly backwards. (shrink)

Epistemic responsibility involves at least two central ideas. (V) To be epistemically responsible is to display the virtue(s) epistemic internalists take to be central to justification (e.g., coherence, having good reasons, fitting the evidence). (C) In normal (non-skeptical)circumstances and in thelong run, epistemic responsibility is strongly positively correlated with reliability. Sections 1 and 2 review evidence showing that for a wide range of real-world problems, the most reliable, tractable reasoning strategies audaciously flout the internalist''s epistemic virtues. In Section 3, I (...) argue that these results force us to give up either (V), our current conception of what it is to be epistemically responsible, or (C) the responsibility-reliability connection. I will argue that we should relinquish (V). This is likely to reshape our epistemic practices. It will force us to alter our epistemic judgments about certain instances of reasoning, to endorse some counterintuitive epistemic prescriptions, and to rethink what it is for cognitive agents to be epistemically responsible. (shrink)

A heuristic is a rule of thumb. In psychology, heuristics are relatively simple rules for making judgments. A fast heuristic is easy to use and allows one to make judgments quickly. A frugal heuristic relies on a small fraction of the available evidence in making judgments. Typically, fast and frugal heuristics (FFHs) have, or are claimed to have, a further property: They are very reliable, yielding judgments that are about as accurate in the long run as ideal non-fast, non-frugal rules. (...) This paper introduces some well-known examples of FFHs, raises some objections to the FFH program, and looks at the implications of those parts of the FFH program about which we can have some reasonable degree of confidence. (shrink)

Gerd Gigerenzer and Thomas Sturm have recently proposed a modest form of what they describe as a normative, ecological and limited naturalism. The basic move in their argument is to infer that certain heuristics we tend to use should be used in the right ecological setting. To address this argument, we first consider the case of a concrete heuristic called Take the Best (TTB). There are at least two variants of the heuristic which we study by making explicit the choice (...) functions they induce, extending these variants of TTB beyond binary choice. We argue that the naturalistic argument can be applied to only one of the two variants of the heuristic; we also argue that the argument for the extension requires paying attention to other “rational” virtues of heuristics aside from efficacy, speed, and frugality. This notwithstanding, we show that there is a way of extending the right variant of TTB to obtain a very well behaved heuristic that could be used to offer a stronger case for the naturalistic argument (in the sense that if this heuristic is used, it is also a heuristic that we should use). The second part of the article considers attempts to extending the naturalistic argument from algorithms dealing with inference to heuristics dealing with choice. Our focus is the so-called Priority Heuristic, which we extend from risk to uncertainty. In this setting, the naturalist argument seems more difficult to formulate, if it remains feasible at all. Normativity seems in this case extrinsic to the heuristic, whose main virtue seems to be its ability to describe actual patterns of choice. But it seems that a new version of the naturalistic argument used with partial success in the case of inference is unavailable to solve the normative problem of whether we should exhibit the patterns of choice that we actually display. (shrink)

The study of rationality and practical reason, or rationality in action, has been central to Western intellectual culture. In this invigorating book, John Searle lays out six claims of what he calls the Classical Model of rationality and shows why they are false. He then presents an alternative theory of the role of rationality in thought and action. A central point of Searle's theory is that only irrational actions are directly caused by beliefs and desires—for example, the actions of a (...) person in the grip of an obsession or addiction. In most cases of rational action, there is a gap between the motivating desire and the actual decision making. The traditional name for this gap is "freedom of the will." According to Searle, all rational activity presupposes free will. For rationality is possible only where one has a choice among various rational as well as irrational options. Unlike many philosophical tracts, Rationality in Action invites the reader to apply the author's ideas to everyday life. Searle shows, for example, that contrary to the traditional philosophical view, weakness of will is very common. He also points out the absurdity of the claim that rational decision making always starts from a consistent set of desires. Rational decision making, he argues, is often about choosing between conflicting reasons for action. In fact, humans are distinguished by their ability to be rationally motivated by desire-independent reasons for action. Extending his theory of rationality to the self, Searle shows how rational deliberation presupposes an irreducible notion of the self. He also reveals the idea of free will to be essentially a thesis of how the brain works. (shrink)

Although Considered By A Few Critics That The Sentence Structures Of The Book Are Quite Incomprehensible And Almost Unbearable To Read, The Book Is An Essential ...

Role of the entrepreneur in a distinct role of profit.

Classic analysis of the subject and the development of personal probability; one of the greatest controversies in modern statistcal thought.

It is widely held that Bayesian decision theory is the final word on how a rational person should make decisions. However, Leonard Savage--the inventor of Bayesian decision theory--argued that it would be ridiculous to use his theory outside the kind of small world in which it is always possible to "look before you leap." If taken seriously, this view makes Bayesian decision theory inappropriate for the large worlds of scientific discovery and macroeconomic enterprise. When is it correct to use Bayesian (...) decision theory--and when does it need to be modified? Using a minimum of mathematics, Rational Decisions clearly explains the foundations of Bayesian decision theory and shows why Savage restricted the theory's application to small worlds. The book is a wide-ranging exploration of standard theories of choice and belief under risk and uncertainty. Ken Binmore discusses the various philosophical attitudes related to the nature of probability and offers resolutions to paradoxes believed to hinder further progress. In arguing that the Bayesian approach to knowledge is inadequate in a large world, Binmore proposes an extension to Bayesian decision theory--allowing the idea of a mixed strategy in game theory to be expanded to a larger set of what Binmore refers to as "muddled" strategies. Written by one of the world's leading game theorists, Rational Decisions is the touchstone for anyone needing a concise, accessible, and expert view on Bayesian decision making. (shrink)

It is widely held that Bayesian decision theory is the final word on how a rational person should make decisions. However, Leonard Savage--the inventor of Bayesian decision theory--argued that it would be ridiculous to use his theory outside the kind of small world in which it is always possible to "look before you leap." If taken seriously, this view makes Bayesian decision theory inappropriate for the large worlds of scientific discovery and macroeconomic enterprise. When is it correct to use Bayesian (...) decision theory--and when does it need to be modified? Using a minimum of mathematics, Rational Decisions clearly explains the foundations of Bayesian decision theory and shows why Savage restricted the theory's application to small worlds. The book is a wide-ranging exploration of standard theories of choice and belief under risk and uncertainty. Ken Binmore discusses the various philosophical attitudes related to the nature of probability and offers resolutions to paradoxes believed to hinder further progress. In arguing that the Bayesian approach to knowledge is inadequate in a large world, Binmore proposes an extension to Bayesian decision theory--allowing the idea of a mixed strategy in game theory to be expanded to a larger set of what Binmore refers to as "muddled" strategies. Written by one of the world's leading game theorists, Rational Decisions is the touchstone for anyone needing a concise, accessible, and expert view on Bayesian decision making. (shrink)